ASCEE/lasp
ASCEE/lasp
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Updated tests
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This commit is contained in:
Anne de Jong 2023-01-12 20:31:55 +01:00
parent 3da6595b0c
commit d1dea1483f
3 changed files with 48 additions and 50 deletions
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7
test/test_biquadbank.py → examples/example_biquadbank.py
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@ -2,15 +2,10 @@
import numpy as np import numpy as np
from lasp import SeriesBiquad, AvPowerSpectra from lasp import SeriesBiquad, AvPowerSpectra
from lasp.filter import SPLFilterDesigner from lasp.filter import SPLFilterDesigner
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from scipy.signal import sosfreqz from scipy.signal import sosfreqz
# plt.close('all') plt.close('all')
# def test_cppslm2():
# """
# Generate a sine wave, now A-weighted
# """
fs = 48000 fs = 48000
omg = 2*np.pi*1000 omg = 2*np.pi*1000

2
test/test_aps.py
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@ -8,8 +8,6 @@ Created on Mon Jan 15 19:45:33 2018
import numpy as np import numpy as np
from lasp import AvPowerSpectra, Window from lasp import AvPowerSpectra, Window
import matplotlib.pyplot as plt
# plt.close('all')
def test_aps1(): def test_aps1():
nfft = 16384 nfft = 16384

21
test/test_cppslm.py
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@ -2,7 +2,7 @@
import numpy as np import numpy as np
from lasp import cppSLM from lasp import cppSLM
from lasp.filter import SPLFilterDesigner from lasp.filter import SPLFilterDesigner
import matplotlib.pyplot as plt
def test_cppslm1(): def test_cppslm1():
""" """
@ -11,7 +11,8 @@ def test_cppslm1():
fs = 48000 fs = 48000
omg = 2 * np.pi * 1000 omg = 2 * np.pi * 1000
slm = cppSLM.fromBiquads(fs, 2e-5, 1, 0.125, [1.,0,0,1,0,0]) slm = cppSLM.fromBiquads(fs, 2e-5, 1, 0.125,
np.array([[1., 0, 0, 1, 0, 0]]).T)
t = np.linspace(0, 10, 10 * fs, endpoint=False) t = np.linspace(0, 10, 10 * fs, endpoint=False)
@ -40,7 +41,10 @@ def test_cppslm2():
omg = 2 * np.pi * 1000 omg = 2 * np.pi * 1000
filt = SPLFilterDesigner(fs).A_Sos_design() filt = SPLFilterDesigner(fs).A_Sos_design()
slm = cppSLM.fromBiquads(fs, 2e-5, 0, 0.125, filt.flatten(), [1.,0,0,1,0,0]) slm = cppSLM.fromBiquads(fs, 2e-5, 0, 0.125,
filt.flatten(), # Pre-filter coefs
np.array([[1., 0, 0, 1, 0, 0]]).T # Bandpass coefs
)
t = np.linspace(0, 10, 10 * fs, endpoint=False) t = np.linspace(0, 10, 10 * fs, endpoint=False)
@ -60,12 +64,15 @@ def test_cppslm2():
# (Fast, Slow etc) # (Fast, Slow etc)
assert np.isclose(out[-1, 0], level, atol=1e-2) assert np.isclose(out[-1, 0], level, atol=1e-2)
def test_cppslm3(): def test_cppslm3():
fs = 48000 fs = 48000
omg = 2 * np.pi * 1000 omg = 2 * np.pi * 1000
filt = SPLFilterDesigner(fs).A_Sos_design() filt = SPLFilterDesigner(fs).A_Sos_design()
slm = cppSLM.fromBiquads(fs, 2e-5, 0, 0.125, filt.flatten(), [1.,0,0,1,0,0]) slm = cppSLM.fromBiquads(fs, 2e-5, 0, 0.125,
filt.flatten(),
np.array([[1., 0, 0, 1, 0, 0]]).T)
t = np.linspace(0, 10, 10 * fs, endpoint=False) t = np.linspace(0, 10, 10 * fs, endpoint=False)
in_ = 10 * np.sin(omg * t) * np.sqrt(2) + np.random.randn() in_ = 10 * np.sin(omg * t) * np.sqrt(2) + np.random.randn()
@ -74,16 +81,14 @@ def test_cppslm3():
# Compute overall level # Compute overall level
level = 20 * np.log10(rms / 2e-5) level = 20 * np.log10(rms / 2e-5)
# Output of SLM # Output of SLM
out = slm.run(in_) out = slm.run(in_)
Lpeak = 20 * np.log10(np.max(np.abs(in_) / 2e-5)) Lpeak = 20 * np.log10(np.max(np.abs(in_) / 2e-5))
Lpeak Lpeak
slm.Lpeak() slm.Lpeak()
assert np.isclose(out[-1,0], slm.Leq()[0][0], atol=1e-2) assert np.isclose(out[-1, 0], slm.Leq()[0], atol=1e-2)
assert np.isclose(Lpeak, slm.Lpeak()[0][0], atol=2e0) assert np.isclose(Lpeak, slm.Lpeak()[0], atol=2e0)
if __name__ == '__main__': if __name__ == '__main__':